Cell Fate Decision as High-Dimensional Critical State Transition.
about
Single-cell entropy for accurate estimation of differentiation potency from a cell's transcriptomeSingle-Cell-Based Analysis Highlights a Surge in Cell-to-Cell Molecular Variability Preceding Irreversible Commitment in a Differentiation Process.Cell population structure prior to bifurcation predicts efficiency of directed differentiation in human induced pluripotent cellsIntegrated time-lapse and single-cell transcription studies highlight the variable and dynamic nature of human hematopoietic cell fate commitment.Quantifying critical states of complex diseases using single-sample dynamic network biomarkers.Uncovering Gene Regulatory Networks Controlling Plant Cell Differentiation.Stem Cell Differentiation as a Non-Markov Stochastic Process.Dynamics of lineage commitment revealed by single-cell transcriptomics of differentiating embryonic stem cells.Inferring gene regulatory networks from single-cell data: a mechanistic approach.Single-cell analysis resolves the cell state transition and signaling dynamics associated with melanoma drug-induced resistance.Individual-specific edge-network analysis for disease prediction.The emerging landscape of in vitro and in vivo epigenetic allelic effects.Detecting the tipping points in a three-state model of complex diseases by temporal differential networks.Gravity Constraints Drive Biological Systems Toward Specific Organization Patterns: Commitment of cell specification is constrained by physical cues.Statistical and integrative system-level analysis of DNA methylation data.Systems Biology Approach and Mathematical Modeling for Analyzing Phase-Space Switch During Epithelial-Mesenchymal Transition.DNA helix: the importance of being AT-rich.Automated cell cycle and cell size measurements for single-cell gene expression studies.Conceptual Challenges of the Systemic Approach in Understanding Cell Differentiation.Reprogramming cell fate with artificial transcription factors.Criticality in cell differentiation.Dynamic network biomarker indicates pulmonary metastasis at the tipping point of hepatocellular carcinoma.Taking Systems Medicine to Heart.Aging in a Relativistic Biological Space-Time.Network-Based Predictors of Progression in Head and Neck Squamous Cell Carcinoma.Correcting the Mean-Variance Dependency for Differential Variability Testing Using Single-Cell RNA Sequencing DataTransition state characteristics during cell differentiationBridging the Data Gap From Toxicity Testing to Chemical Safety Assessment Through Computational ModelingIdentification of Biologically Essential Nodes via Determinative Power in Logical Models of Cellular ProcessesDetermining Relative Dynamic Stability of Cell States Using Boolean Network ModelSingle cell RNA-seq and ATAC-seq analysis of cardiac progenitor cell transition states and lineage settlement
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P2860
Cell Fate Decision as High-Dimensional Critical State Transition.
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
Cell Fate Decision as High-Dimensional Critical State Transition.
@ast
Cell Fate Decision as High-Dimensional Critical State Transition.
@en
type
label
Cell Fate Decision as High-Dimensional Critical State Transition.
@ast
Cell Fate Decision as High-Dimensional Critical State Transition.
@en
prefLabel
Cell Fate Decision as High-Dimensional Critical State Transition.
@ast
Cell Fate Decision as High-Dimensional Critical State Transition.
@en
P2093
P2860
P1433
P1476
Cell Fate Decision as High-Dimensional Critical State Transition.
@en
P2093
Alessandro Giuliani
Hannah Chang
Ivan G Castaño
Joseph Zhou
Kalliopi Trachana
Mitra Mojtahedi
Rebecca Y Y Leong-Quong
P2860
P304
P356
10.1371/JOURNAL.PBIO.2000640
P407
P577
2016-12-27T00:00:00Z